WO2019119256A1 - 一种实时发布路内停车服务指数方法及系统 - Google Patents

一种实时发布路内停车服务指数方法及系统 Download PDF

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WO2019119256A1
WO2019119256A1 PCT/CN2017/117094 CN2017117094W WO2019119256A1 WO 2019119256 A1 WO2019119256 A1 WO 2019119256A1 CN 2017117094 W CN2017117094 W CN 2017117094W WO 2019119256 A1 WO2019119256 A1 WO 2019119256A1
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parking
street parking
street
road
model
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PCT/CN2017/117094
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French (fr)
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关金平
须成忠
关志超
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深圳先进技术研究院
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Publication of WO2019119256A1 publication Critical patent/WO2019119256A1/zh

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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled

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  • the present application relates to the field of intelligent transportation technologies, and in particular, to a method and system for releasing an on-street parking service index in real time.
  • Roadside parking is the most intuitive reflection of urban traffic management. Most cities in the world have listed roadside parking as one of the priority development priorities. Due to the limitation of urban land resources, the demand for static traffic cannot be satisfied by the construction of off-street parking lots. At the same time, the on-street parking mode of urban road traffic network is due to its own advantages, such as convenient parking and short walking distance. It is widely welcomed by vehicle drivers. A large number of research results show that 30% of the vehicles in the urban central area traffic are looking for parking spaces, and 20% of the vehicles in the whole city road network traffic are looking for parking spaces and causing traffic congestion.
  • the urban road parking system was planned and designed.
  • the data related to the berth demand characteristics are still obtained through relatively extensive statistical methods. There are still no corresponding statistical means for detailed and dynamic parking features such as different regions, different land types, different time periods and different parking purposes. There are certainly large differences in the characteristics of residents' travel and attraction in schools, business districts, residential areas, large public events, etc. These characteristic areas will also reflect the need for differentiated parking. In addition, for the calculation of the berth parking turnover rate of different road sections (the national standard generally takes 7-9 vehicles/day), there is also a large error, and this index is a key factor for directly evaluating and predicting the parking berth demand. In addition, demand characteristics at different time periods, including peak hours and off-peak hours, need to be treated differently during the day and night.
  • the parking order is chaotic, the berth setting is lacking in overall planning and planning, and the parking gradient price is difficult to play.
  • on-street parking berths are located on the branch roads and the secondary roads, they affect the function of the traffic micro-circulation system; the existing pedestrian passages and non-motor vehicle lanes are crowded by berths; The setting of the position, the planned slow traffic passage is also difficult to implement; often the road berth is set near the intersection and the bus station, which affects traffic safety.
  • On-street parking in concentrated areas of residential areas is obviously charging for the rigid parking demand of nearby residents; while the on-street parking price in commercial concentrated areas does not have obvious staircase effect compared with other areas, and some just channel this part of parking demand. In the off-street parking lot, the people entering these areas have not been fundamentally reduced to choose to use the car, resulting in low berth turnover rate.
  • the parking berth is in a single form, which cannot meet the needs of diversified parking purposes, and the berth utilization rate is low.
  • Parking means that the driver does not leave the car, and makes a short stay for passengers or goods to get on and off; parking means that the driver turns off the car for a longer time or even overnight. Therefore, the indicator should distinguish between a variety of parking forms, such as “no stop / ban”, “no parking can not stop”, "first half of the month banned or the second half of the ban”.
  • Lack of transfer parking facilities There is a big gap in the parking and transfer facilities. If the residents outside the city center area connect to the subway through the car, there is no corresponding parking facility. There are also large gaps in non-motorized parking facilities around the subway station facilities. This part of the non-motorized parking facilities is also relatively simple, lacking sunshade and rain protection facilities, which greatly reduces the residents' choice of non-motor vehicles to solve the "last mile.” "The motivation of the problem.
  • the construction and management of parking facilities have long existed at the municipal level, and the management of funds has not been integrated into the district-level fiscal and taxation system, forming a separation of strips and blocks.
  • the management system has formed the main implementation of business guidance at the municipal level, and the district level is the mode of construction and management.
  • Each district has become the main body of parking facilities construction and management.
  • the management of motor vehicle facilities in some cities was transferred to the Municipal Urban Management Bureau by the Municipal Public Security Bureau (the road enforcement power is still in the Traffic Management Bureau). This has resulted in the parking management agency at the district level having the incentive to increase the supply of berths as much as possible.
  • unified planning and construction management must be carried out at the municipal level.
  • the resources within the width of the red line shall be planned by the urban planning department, but the financial management shall enter the district-level fiscal and taxation.
  • the present application provides a method and system for real-time release of an on-street parking service index, which aims to solve at least one of the above technical problems in the prior art.
  • a method for real-time release of an on-street parking service index including:
  • Step a Establish a vehicle speed retardation model for the on-street parking setting
  • Step b Analyze the delay of the motor vehicle after the parking belt is set in the road;
  • Step c Select the on-street parking zone to set the scale reasonably
  • Step d Plan the parking design of the city road.
  • the technical solution adopted by the embodiment of the present application further includes: before the step a, the method further comprises: establishing an on-street parking service index index system, and providing a scientific basis for the evaluation of the service level and service quality of the on-street parking.
  • the technical solution adopted by the embodiment of the present application further includes: the step a specifically includes: establishing a basic model of the road speed; establishing a friction effect correction model of the road parking zone; and establishing a blocking effect correction model of the road parking zone, wherein
  • the road speed model after the friction effect correction is:
  • Ki--the slope parameter is affected based on the spatial obstacle rate
  • the technical solution adopted by the embodiment of the present application further includes: the step b specifically includes: based on the establishment of the speed block model of the motor vehicle, using the friction effect and the blocking effect as an overall analysis of the interference of the road parking on the road segment of the motor vehicle flow, establishing The corresponding theoretical model analyzes the impact of traffic flow on the road after the on-street parking setting.
  • the technical solution adopted by the embodiment of the present application further includes: the establishing the corresponding theoretical model includes: a deceleration-acceleration delay model, a heel delay model, a heel delay model in the case of a discrete flow, and a heel delay model in a continuous flow situation. , total delay model establishment and vehicle delay model.
  • the technical solution adopted by the embodiment of the present application further includes: the step c specifically includes: setting a vehicle parking player behavior selection model; setting a vehicle parking person cost model; setting a road segment traveler cost model; selecting a reasonable parking scale of the road parking zone; Model algorithm.
  • the technical solution adopted by the embodiment of the present application further includes: the model algorithm of the design specifically includes:
  • Step 11 take the initial step size ri>0, and allow the error e>0;
  • Step 13 Construct a barrier function, and the barrier term can use a derivative function: Or logarithmic function form:
  • Step 14 Take For the initial point, unconstrained minimization of the barrier function (within R0):
  • Step 15 Verify that the convergence criteria are met: or
  • Step 17 Considering the location of the on-street parking zone in the urban traffic network congestion factors, the parking cost increases Y(t)>0;
  • Step 18 Consider the reduced on-street parking cost G(t)>0 for the on- and off-street parking sharing mode.
  • the step d includes: selecting a road section that needs to set an on-street parking, and selecting a process to make a preliminary judgment on whether the road section can set an on-street parking zone according to road traffic conditions and traffic volume conditions.
  • Determining the design goal of on-street parking analyzing the setting conditions; studying the selection of the reasonable position of the on-street parking zone, analyzing the distance between the on-street parking zone and the signalized intersection, the building entrance and exit and the crosswalk, as well as the terrain conditions and special Limitation of traffic environment; study on the design method and applicability of parking berths on the road, and on this basis, investigate whether the setting of the parking zone inside the road meets the design goal. If it is not satisfied, it also needs to redesign the on-street parking. band.
  • a real-time release of an on-street parking service index system includes a system front-end monitoring module and a system background service.
  • the service module, the system data analysis and mining service index module, the on-street parking service index release and sharing module, the system front-end monitoring module is used to complete the collection task of the on-street parking space usage status information
  • the system background service module is used for Constructing an on-street parking management service index platform to realize the use of on-street parking spaces, in-street parking service correction, transaction processing and clearing settlement, parking user management service inspection, information processing report generation and analysis, early warning method visualization, road Internal parking data storage and sharing and/or system operation and maintenance
  • system data analysis and mining service index module is used to complete system operation monitoring, T-GIS electronic map accurate positioning matching, on-street parking space data analysis and/or automatic generation of parking space
  • the report, the on-street parking service index release and sharing module is used for real-time release of the information release and sharing
  • the system front-end monitoring module includes a front-end information collecting terminal such as an in-street parking space geomagnetic coil detector, a radio frequency communication, and a video monitoring.
  • the real-time on-street parking service index method and system of the embodiment of the present application has a service index model that introduces traffic congestion and shared parking environment elements, and is designed to be released in real time.
  • the parking service index system the method for establishing a real-time release of the on-street parking service index, and the development of a real-time release of the on-street parking service index system, the overall solution for the evaluation of the on-street parking service index; the real-time on-street parking service index method of the present application embodiment and
  • the system closely tracks the core problem of urban on-street parking service as an entry point; it is a revolutionary challenge to the traditional questionnaire evaluation of the on-street parking service index in the era of traffic big data; it overcomes the traditional questionnaire-style evaluation of on-street parking.
  • FIG. 1 is a flow chart of a method for real-time release of an on-street parking service index according to a first embodiment of the present application
  • FIG. 2 is a structural block diagram of a method for real-time release of an on-street parking service index according to a first embodiment of the present application
  • FIG. 3 is a flow chart of a method for real-time publishing an on-street parking service index according to a second embodiment of the present application
  • FIG. 4 is a flow chart of a method for real-time release of an on-street parking service index according to a third embodiment of the present application.
  • Figure 5 is a flow chart of on-street parking planning and setting for urban road network
  • FIG. 6 is a schematic structural diagram of a real-time release on-street parking service index system according to an embodiment of the present application.
  • FIG. 7 is a physical structural diagram of a system front-end monitoring module of a real-time release on-street parking service index system according to an embodiment of the present application.
  • FIG. 8 is a structural diagram of a real-time release of an on-street parking service index system information processing flow according to an embodiment of the present application
  • FIG. 9 is a system diagram of a real-time release on-street parking service index system according to an embodiment of the present application.
  • FIG. 10 is a visual query interface diagram of a real-time release on-street parking service index system according to an embodiment of the present application.
  • 11 is a distribution of a radio frequency communication base station of a real-time announcement of an on-street parking service index system according to an embodiment of the present application
  • FIG. 12 is a diagram showing the law enforcement distribution of the inspecting personnel of the on-street parking service index system in the real-time release of the embodiment of the present application.
  • FIG. 1 is a real-time release on-street parking service finger according to a first embodiment of the present application.
  • FIG. 2 is a structural block diagram of a method for real-time release of an on-street parking service index according to a first embodiment of the present application.
  • the real-time release of the on-street parking service index method of the first embodiment of the present application includes the following steps:
  • Step 110 Quantify and analyze the on-street parking feature
  • the on-street parking characteristic quantification is an embodiment of the agglomeration effect of the road traffic parking behavior and the utilization degree of the parking supply facility, reflecting the main characteristics of the city parking, the practical situation of the parking facility, and the parking supply and demand relationship.
  • the quantification of on-street parking characteristics is the main basis for the planning and evaluation of parking facilities.
  • the analysis of on-street parking characteristics can help to plan urban parking facilities, formulate parking policies and management measures, regulate urban parking supply and demand structure, and optimize urban road traffic flow.
  • On-street parking features include the following:
  • the purpose of on-street parking refers to the purpose of parking for the parking lot, such as class, official duties, loading and unloading of goods, shopping, cultural entertainment, pick-up and drop-off, home, catering, etc.
  • the purpose of parking determines the behavior of the parking lot on the road to a certain extent.
  • the planning of on-street parking facilities and the development of parking management measures need to consider the geographical location of different urban areas, the parking spaces in the roads and the parking spaces of surrounding communities, etc.
  • the parking purpose structure will affect the regulation of parking berth supply and demand and parking management policies.
  • the average of the ratio of on-street parking time to actual parking volume of all vehicles in a certain period of time is an important indicator reflecting the use of parking facilities in urban roads.
  • the length of parking time is closely related to the size of the city, the area where the city functions differently, the type of on-street parking facilities, the sharing of on-street parking spaces, and the purpose of parking. Different destinations have different requirements for parking time. At present, no measures have been taken to limit the parking time, resulting in long on-street parking time and low efficiency. Traffic congestion in urban central areas is more serious.
  • the peak parking index refers to the ratio of the total number of parked vehicles to the capacity of parking facilities during peak hours. It reflects the congestion of parking facilities during peak hours and is also an important basis for determining the scale of parking facilities.
  • the berth utilization rate refers to the ratio of the average parking time of each berth to the total berth time in a certain period of time, reflecting the time utilization efficiency of the parking berth, and expressing the congestion degree of the parking facility.
  • the berth turnover rate refers to the average number of vehicles parked in each parking berth within a certain period of time. It is usually expressed as the ratio of the number of accumulated parking vehicles in one day to the capacity of parking facilities, reflecting the space utilization efficiency of parking facility berths.
  • the berth turnover rate of different urban areas, different shared parking spaces and different parking facilities is different, and the berth turnover rate of urban central areas is higher than that of urban peripheral areas.
  • Step 120 Analyze the parking behavior of the on-street parking person
  • the parking behaviors in different areas are also very different.
  • the parking actors are in a certain traffic environment. It also shows the corresponding characteristics.
  • the parking behavior and characteristics reflect the basic characteristics of parking. It is the basic basis for analyzing the relationship between urban parking supply and demand, and analyzing the contradictions of urban parking.
  • the analysis and mastery of on-street parking behavior and characteristics are the urban road parking planning and the on-street parking policy laws and regulations. Important basis.
  • the parking behavior of on-street parking people specifically includes:
  • the process of parking the parking lot is a consumption process.
  • the parking person pays a certain price in exchange for the equivalent parking service.
  • the parking player's selection process also follows the consumer's economic behavior.
  • the parking fee has a serious impact on the parking behavior.
  • the parking personnel type has a great influence on the parking behavior.
  • the parking arrival time reduces the parking cost.
  • the road traffic congestion index price factor directly affects the parking person's behavior.
  • the parking space sharing status is also This will reduce the cost of parking.
  • Parking habits are formed under the influence of personal preferences, social environment, and supply characteristics of parking facilities. Different types of cities have different parking habits, such as the length of parking time and the psychological difference in parking facilities selection. /Middle/small cities have differences in walking distance requirements.
  • the humanistic environment has certain influence on parking behavior. For example, different types of residences correspond to different levels of consumer groups. The higher the level of residential areas, the higher the vehicle ownership rate and the quality requirements for parking services, the more parking the parking users pay attention to.
  • the safety is not sensitive to economic factors; the income of households in low-grade residential areas is relatively low, and the choice of parking services has a greater impact on parking costs than safety.
  • the characteristics of the vehicle directly affect the parking behavior, mainly reflected in the difference in parking behavior between local and foreign cars, buses and private cars, new and old cars, and the price of vehicles. If the foreign vehicle is unfamiliar with the location, charges, etc. of the parking facilities, it is not willing to waste too much time in search of and selection of parking facilities.
  • the parking facilities are often selected based on the nearest destination or according to the habit; the location of the local vehicle to the parking The fees and other conditions are more familiar. The parking lot will make a choice by considering various factors influencing factors.
  • the parking facilities are usually selected based on the principle of maximizing service utility.
  • Step 130 Quantitative analysis of on-street parking facilities and parking behavior
  • the length of parking time of each vehicle is directly related to the efficiency of parking spaces. It is necessary to analyze and study the factors affecting the choice of parking time for parking users, and to adjust the length of parking time and improve the turnover efficiency of parking spaces by using policy factors (such as parking price).
  • the discrete choice logistic model technique is used to establish the relationship model between on-street parking time and parking behavior. Polynomial logistic regression analysis is used to solve the relationship between multiple categorical variables and influencing factors. It is a deep application of discrete behavior selection model for parking behavior.
  • Step 130 specifically includes:
  • Step 131 Quantify and analyze the influencing factors of social public road parking behavior
  • the public parking environment can be divided into parking spaces that make up for inadequate office construction, make up for inadequate commercial allocation, and make up for inadequate hospital construction.
  • the parking time is widely distributed and the parking time will be based on relevant analysis. Correlate analysis with various parking behavior indicators to find out the correlation between parking time and parking purpose, parking price, and parking fee payer, so as to establish a parking behavior model.
  • the probability P3n with the parking time greater than 4 hours is selected as the reference group of P1n and P2n, and the parking time selection model is established. Therefore, the parking time is the dependent variable, the parking purpose, the parking fee payer as the categorical variable, and the parking price as a continuous variable into the model, the results are as follows:
  • Cost in -- the nth parking lot selects the parking space price for the length i;
  • Step 132 Establish a commercial on-street parking behavior model
  • the main purpose of commercial parking is for entertainment and leisure.
  • the parking fee payer mainly pays for the individual.
  • the parking time is analyzed with the parking behavior indicators. It is concluded that the parking time has obvious relationship with the parking purpose and parking price. Under the conditions of the payer, find out the main factors that affect the parking time.
  • the probability P3n with the parking time greater than 4 hours is selected as the reference group of P1n and P2n, and the parking time selection model is established. Therefore, the parking time is the dependent variable, the parking purpose is taken as the categorical variable, and the parking price is substituted into the model as a continuous variable.
  • Cost in -- the nth parking lot selects the parking space price for the length i;
  • Step 133 Establish an on-street parking behavior model
  • the main purpose of parking for office parking is for work, the payers of parking fees are mainly paid for the unit, and the personal payment is also a certain percentage. Correlate the parking time with each parking behavior indicator and get a stop There is a clear relationship between the time of the car and the purpose of parking and the price of the parking. Under the conditions of different payers, the main factors affecting the parking time are found out.
  • the probability P3n with the parking time greater than 6 hours is selected as the reference group of P1n and P2n, and the parking time selection model is established. Therefore, the parking time is the dependent variable, the parking purpose is taken as the categorical variable, and the parking price is substituted into the model as a continuous variable.
  • Cost in -- the nth parking lot selects the parking space price for the length i;
  • Step 140 Modeling the on-street parking demand prediction.
  • parking demand has daytime parking demand and night parking demand.
  • Daytime parking demand is to meet the needs of various social and economic activities, mainly for social parking demand, urban road parking space.
  • the high usage rate is also a derivative demand for transportation behavior;
  • the night parking demand is the parking demand caused by vehicle ownership and night activities, mainly for basic parking demand, because most night parking demand is for residents or unit vehicles at night.
  • the night parking demand is relatively fixed, and the purpose of travel is relatively simple.
  • Vehicle parking is a product of urban social, economic, humanities and transportation development to a certain extent.
  • the demand for parking in urban roads is affected by many aspects, including the following contents:
  • the road parking demand forecasting modeling method specifically includes
  • Step 141 Establish a parking generation rate model
  • Parking Generation Rates refer to the number of parking spaces required for a unit of land use indicator.
  • the parking generation rate model is based on the relationship between land use properties and parking demand generation rate.
  • the technical route is to treat various land-use plots in the region as parking attraction sources, while regional total parking.
  • the demand is equal to the sum of the attractive amounts of these individual plots.
  • the parking generation rate model is as follows:
  • Step 142 Establish a land use and traffic impact analysis model
  • the land use and traffic impact analysis model is based on the fact that urban parking demand is closely related to the economic activity characteristics and traffic characteristics of the region. Through surveys on parking characteristics and land use properties, Starting from the status quo of motor vehicle ownership, land use and its changing trends, determine their relationship with parking demand, and then analyze the current parking demand and forecast future parking demand.
  • the model is an extension of the parking generation rate model. It not only has the characteristics of the generation rate model, but also combines the parking generation rate with the road traffic volume, and better balances the relationship between parking and land use and transportation.
  • the model is as follows:
  • Xi--The land use scale of the i-th region can be expressed by the corresponding different types of land use, or by the number of employees responding to different types of land use;
  • Step 143 Establish a land analysis model
  • the land use analysis model also known as the commercial land parking analysis model, is based on the relationship between the parking demand and the nature of the land and the number of employees to forecast the parking demand for the future planning year.
  • the basic assumption is that in a business-oriented area, long-term parking demand is caused by employees traveling to work, and short-term parking demand is caused by commercial activities in the area.
  • the specific prediction model is:
  • di--the i-zone peak parking demand (number of berths);
  • Step 144 Establish a travel attraction model
  • the generation of parking demand is related to the economic and social strength of the region, and the socio-economic intensity is closely related to the number of trips attracted by the region.
  • the principle of the travel attraction model is to establish the relationship between the number of parking spaces required for peak hour parking and the attraction of regional motor vehicle travel.
  • the basic conditions for modeling are to carry out urban comprehensive traffic planning survey, according to the travel distribution model of each traffic community and the The mathematical model of the parking attraction is established, and the predicted data of obtaining the parking number is derived.
  • the parking demand model is as follows:
  • Step 145 Establish a multiple regression analysis prediction model
  • the regression analysis model is based on the historical data of related variables for several years, and the regression coefficient is used to calculate the regression coefficient value, and the statistical test is performed. At the same time, the future value of each influencing factor is predicted by the linear trend prediction method, and the regression formula can be substituted to predict the future parking demand.
  • the specific prediction model is:
  • Ki--regression coefficient, i 1, 2, 3, 4, 5, 6, ....
  • Step 146 Establish a traffic volume-parking demand model.
  • the parking demand in any area is necessarily the result of the attraction of the vehicles arriving in the area.
  • the parking demand parking space is a certain percentage of the traffic passing through the area. If the land use function in the area is relatively balanced and stable, the prediction of modeling is more reliable.
  • the specific model is:
  • Traffic volume--The parking demand model has a simple prediction method and clear thinking. It is suitable for short-term prediction of land use function balance and stable areas. The model ignores the deviation of parking generation rate of different types of vehicles, and does not reflect the impact of changes in traffic flow composition caused by traffic policies or control measures on parking demand. Moreover, it is impossible to obtain specific areas by using traffic volume-parking demand model for prediction. The amount of parking facilities required for each land use, so this model is only used as a method to verify the prediction results of other prediction models.
  • FIG. 3 is a flowchart of a method for real-time publishing an on-street parking service index according to a second embodiment of the present application.
  • the real-time release of the on-street parking service index method of the second embodiment of the present application includes the following steps:
  • Step 210 Establish an on-street parking service index indicator system
  • step 210 the real-time release of the on-street parking service index method for traffic congestion and shared parking environment is based on the basic characteristics of on-street parking, establishing an indicator system for the relevant service index, and providing an assessment of the service level and service quality of on-street parking.
  • Scientific basis including the following indicators:
  • Parking supply refers to the number of parking spaces that may be provided in a certain on-street parking area. The measurement of parking supply is indicated by the actual number of parking spaces in the survey.
  • Parking demand refers to the amount of parking attraction at a specific time interval within a given parking area, expressed as the number of parking during the peak period of the representative destination.
  • Parking facility capacity refers to the maximum number of berths that can be legally parked at the same time in a given parking area or the effective area of the parking lot, usually expressed by the number of vehicles.
  • Walking distance refers to the actual walking distance from parking to the destination of travel, usually in meters; it can reflect the convenience of parking facilities layout for parking vehicles, and also the planning of parking system and the release of parking information. One of the important control factors.
  • Accumulated parking volume refers to the number of vehicles parked in parking facilities within a certain period of time.
  • Parking time refers to the actual parking time of the vehicle in the road parking space. It is one of the basic indicators to measure the traffic load and turnover efficiency of the parking belt. Its distribution is related to the purpose of parking, land use and other factors.
  • Parking saturation refers to the ratio of the number of vehicles actually parked at a certain time to the capacity of parking facilities, reflecting the congestion level of parking facilities. The ratio of the number of parking spaces during peak hours to the capacity of parking facilities is called peak parking saturation.
  • Berth turnover rate refers to the average number of parking hours of the unit parking berth during working hours. The space utilization efficiency of the parking berth is reflected by the frequency of parking berths occupied by the vehicle.
  • Berth utilization rate refers to the ratio of the actual occupied time of each parking berth to the total working time during working hours, reflecting the time utilization efficiency of parking berths.
  • Delayed parking number refers to the total number of parking spaces in a survey point or area at a certain time interval, that is, the sum of the number of vehicles that are delayed during each interval observation period, and the unit is the number of vehicles.
  • Average delay time It means the average parking time of all actual parked vehicles.
  • the average delay time is the total delay time divided by the actual number of parked vehicles.
  • Parking density refers to the basic unit of measurement of parking load. It not only indicates the extent to which the amount of parking attraction varies with time, but also the highest parking density during peak hours; it also indicates its spatial distribution, and the amount of parking at different attraction points. The extent of the size.
  • Step 220 Analyze the influence of the on-street parking on the traffic flow in the urban road section
  • step 220 the influence of the on-street parking on the traffic flow on the urban road section mainly includes two parts:
  • the entry and exit of vehicles parked in the 2nd road may block the traffic flow inside the road. Especially when the road traffic volume is large, the vehicle entering and exiting often does not complete the traversable traffic flow gap, but forcibly crosses. It causes great disturbance to the vehicles on the road section and even causes traffic jams, the so-called block effect.
  • Step 230 Establish a traffic flow delay model
  • the motor vehicle flow is set
  • the parking zone in front of the road is relatively stable. Because there is no obstacle in the non-motor vehicle lane, the motor vehicle and the non-motor vehicle interfere with each other less, and the motor vehicle runs at normal speed ( ⁇ f).
  • ⁇ f normal speed
  • the in-street parking zone is set, the non-motor vehicle saturation is improved because the non-motor vehicle lane has an in-street parking belt setting. In order to get rid of mutual constraints, non-motor vehicles often drive into motor vehicles.
  • the running state of the road section can be described as: “Advance by the normal speed of the section ( ⁇ f) ⁇ deceleration ( ⁇ ′) enters the on-street parking zone ⁇ to form a mixed vehicle and non-motor vehicle Speed ( ⁇ b) forward ( ⁇ b is defined as the parallel stroke speed under the combined effect of the machine and the non-mixed line and the parking belt vehicle reaching the exit block) ⁇ Acceleration ( ⁇ ) leaving the on-street parking zone ⁇ Re-stable speed ( ⁇ e )go ahead”.
  • the speed change intuitively reflects the blockage situation before and after parking in the road.
  • the delay reflects the road benefit loss before and after the installation, which is the most direct basis for setting the on-street parking.
  • Step 240 Matching the shared on-street parking zone and the off-street parking lot
  • On-street parking belts and off-street parking lots are indispensable components of public parking lots.
  • the location of on-street parking belts is close to the destination of travel, with high convenience and high turnover rate, but at the same time forming traffic flow on the road.
  • the activity bottleneck has a greater impact on other travellers; the location of the off-street parking lot is far from the travel destination, the convenience is weak, and the turnover rate is low, but it has less impact on other travellers on the road. Therefore, how to find a reasonable matching relationship between the on-street parking zone and the berth setting of the off-street parking lot can not only ensure better parking convenience, but also control the influence of other travelers on the road section within a certain range.
  • the maximization of total benefits is the focus of the reasonable setting of on-street parking.
  • FIG. 4 is a flowchart of a method for real-time publishing an on-street parking service index according to a third embodiment of the present application.
  • the real-time release of the on-street parking service index method of the third embodiment of the present application includes the following steps:
  • Step 310 Establish a vehicle speed block model for the on-street parking setting
  • the on-street parking utilizes the road space resource as the parking carrier, and has the advantages of flexible setting, low construction cost, small occupied space, and convenient directness compared with the off-street parking facility.
  • on-street parking not only uses the road as its parking space, but also as the passage for its entry and exit, the impact on the traffic flow state of the road section is also the most direct.
  • Road car based on road traffic load level The establishment of the speed (or time) relationship model helps to adjust the degree of influence on the traffic flow of the road section after the parking lot is set.
  • the vehicle is Non-motor vehicles have an impact, and should focus on the traffic blockage and delay caused by motor vehicle flow; and after the parking space is set at the non-motor vehicle farm, there are mainly three roads and four roads with the road section.
  • the parking lot is set up It mainly affects non-motor vehicles. When considering the setting conditions, it mainly starts from the influence of the non-motor vehicle lanes after installation, and has less influence on the motor flow of the road sections.
  • Step 310 specifically includes:
  • the basic relationship between the vehicle speed and the road traffic is based on the road.
  • the resistance function model fits the statistical data in the form of:
  • i--Types of traffic operation variables including co-directional vehicles, co-directional non-motor vehicles, opposite vehicles, and non-motor vehicles.
  • the friction effect of the on-street parking belt on the traffic flow of the road section is mainly reflected by Rb.
  • Different space obstacle rates Rb will have different friction effects on the road dynamic traffic flow. With the increase of Rb, the frictional resistance between road traffic increases, the road The traffic flow rate will drop.
  • the road speed model after the friction effect correction is:
  • ki--based on the spatial obstacle rate affects the slope parameter.
  • the blocking effect of on-street parking has a frictional effect on the one hand, and on the other hand, it is affected by the way of entering, exiting and stopping the way of parking in the road. Therefore, the block effect mentioned here refers to the blockage of the vehicle flow in and out of the road on the basis of the friction effect.
  • the block effect is mainly manifested by different time barrier rates RT. As the RT increases, the road traffic flow speed decreases.
  • the correction model considering the friction effect and the blocking effect is:
  • Step 320 Analyze the delay of the motor vehicle after the parking lane is set in the road;
  • step 320 on the basis of the establishment of the vehicle speed retardation model, considering the different vehicle traffic flow arrival conditions, the friction effect and the blocking effect are used as a whole to analyze the interference of the road parking on the road segment motor vehicle flow, and establish corresponding
  • the theoretical model analyzes the impact of traffic flow on the road after the on-street parking setting. Establish corresponding theoretical models including:
  • the average speed of the normal driving of a certain section of the road is ⁇ f km/h
  • the average deceleration of the vehicle is ⁇ 'm/s-2
  • the speed of the vehicle in the on-street parking zone is ⁇ b km/h
  • the distance s from the average speed ⁇ f to the following speed ⁇ b is:
  • the deceleration time t1 of the vehicle from the normal running average speed ⁇ f to the following speed of the vehicle in the on-street parking zone is ⁇ b:
  • the time when the vehicle drives the deceleration distance s at the normal average driving speed is:
  • the deceleration delay of the vehicle from the normal running average speed ⁇ f to the following speed ⁇ b is:
  • the average speed of the vehicle in a certain section is set to ⁇ m/s-2, and the final speed of the vehicle acceleration is ⁇ e, and the acceleration delay dd of the vehicle can be obtained as:
  • the bicycle will often occupy the motor vehicle lane in order to overtake the bicycle in front of it, which will make the motor vehicle unable to have the road width condition beyond the bicycle in front of it, and has to follow the bicycle.
  • the speed at this time is much lower than the normal driving speed, and the running time in the car-passing process is more than the normal driving speed through the running time of the speeding section, thereby causing the delay of the car.
  • the traffic density in the road is not large, the mutual influence between the vehicles is weak, and the arrival of the vehicles before and after is independent. At this time, the arrival of the traffic flow is random, and the probability model can be used to describe a certain section of the road at a certain time. The number of vehicles arriving within the interval. When the traffic density is large, there are mutual constraints between the vehicles, and the arrival of the front and rear vehicles is not independent. At this time, the traffic flow has the continuity characteristics of the fluid, and the fluid mechanics theory is used to describe the condition of the traffic flow.
  • the traffic density in the road is not large and the traffic flow arrives randomly, the number of vehicles arriving within a certain time interval can be regarded as a random variable, and the discrete variable is used to describe such random variables.
  • the Poisson distribution can better describe the arrival between vehicles. Therefore, the traffic flow is set to obey the Poisson distribution.
  • the probability Pk( ⁇ t) of reaching k vehicles in the time ⁇ t is:
  • the average time spent by the customer in the system is equal to the average number of customers in the system divided by the customer arrival rate, ie the expected number of customers in the system: Set the length of the parking belt in the road to L.
  • the delay of the following operation caused by the machine and the non-mixing line is:
  • the delay D due to the internal and non-mixed lines of the road segment is:
  • Traffic flow can use fluid mechanics theory to describe the flow of traffic.
  • the time required for the first car to finish the on-street parking zone is tf. After the traffic enters the on-street parking zone, the formed tail of the team moves backwards at a speed of ⁇ 1, and the head of the crowded team advances at a speed of ⁇ b.
  • the function of the number of vehicles in the road parking zone with time t is: In the time micro segment (t, t + ⁇ t), it can be considered that the number of crowded vehicles is equal to n(t), and the distance traveled by each vehicle is ⁇ b ⁇ t.
  • the delay due to congestion is:
  • the total delay ⁇ d of n(t) vehicle t to t+ ⁇ t is:
  • the following delay in Df1 during the period from 0 to tf is:
  • the delay of Df2 during the 2tf period is: The delay in the following period can be followed by the technical route of the above delay.
  • Dfn the delay of Dfn
  • the total follow-up delay Dnf is calculated from 0 to ntf.
  • the number of crowded vehicles Nmti generated during a statistical interval tt is:
  • the resulting follow-up delay Dt is:
  • the total delay caused by friction and blockage of motor vehicle flow includes three parts: deceleration delay, follow-up delay and acceleration delay.
  • deceleration delay For the case of discrete traffic flow, the total delay of the unit duration on the road section is Dt, and the discrete traffic flows down the bicycle.
  • the delay of the follow-up is dt, then the total delay of the discrete flow in the area affected by the on-street parking zone is 1 hour:
  • ⁇ i , ⁇ i the arrival rate and departure rate of the vehicle
  • Nmti--unit counts the number of times of crowded vehicles
  • Step 330 Select an on-street parking zone to reasonably set the scale
  • step 330 specifically includes:
  • Step 331 Setting a vehicle parking behavior selection model
  • on-street parking arrives at Burson distribution, and the time of service is stopped. The time obeys the negative exponential distribution. It is assumed in the parking behavior selection model that the vehicle parker prefers the on-street parking zone. When the parking lot is full, the later vehicles will additionally look for the off-street parking lot and will not wait in line for the vacancy. Therefore, the behavior of the vehicle parker can be selected as a loss of the Bosson distribution/negative exponential distribution/N service desks to the queuing system.
  • the driver's arrival obeys the Poisson distribution with the parameter ⁇
  • the driver's service time obeys the negative exponential distribution with the parameter ⁇
  • the destination is the service desk within the P.
  • Step 332 Set a vehicle parking cost model
  • the cost function defining the vehicle parker is S (inside P), which includes the difference in parking time and parking cost between off-street parking and on-street parking, and the influence of congestion on the urban road network in which the parking zone is located.
  • S the cost function defining the vehicle parker
  • Zj the number of vehicles (vehicles/hour) that are turned to the off-street parking lot by the on-street parking belt in the unit time;
  • A--the average unit time value of the car traveler (yuan/(person ⁇ hour));
  • M the average number of passengers per car (person/pcu);
  • G(t)--Intra-road and off-street parking spaces share increased revenue (yuan).
  • Step 333 The effect of setting the on-street parking after the dynamic traffic is mainly reflected in reducing the road traffic capacity and increasing the load of the road, thereby affecting the travel speed of other car travelers, causing delays and increasing travel costs. .
  • N (in P) added to other travellers, and increase the travel cost incurred by other travellers in the road section due to delays in the road parking zone.
  • N (P) increases with the on-street parking scale. Increase.
  • N(P ⁇ ) AmD t +f 1 (t))+Y(t)-G(t);
  • Dt--Set the total hour delay (hours) of the on-street parking belt to the traffic flow of the road section.
  • Step 334 Select a reasonable scale of the on-street parking zone
  • the optimal scale of the on-street parking belt is to find a reasonable matching relationship between the on-street parking zone and the off-street parking lot when the total system cost is the smallest.
  • the parking cost of parking lots gradually decreases with the increase of on-street parking scale.
  • the travel costs of other travellers in non-parking sections gradually change with the increase of the scale of on-street parking spaces. Large, so for the total social cost, that is, the parking cost of the parking lot and the other non-traveler travel costs, there must be a minimum, corresponding to the optimal on-street parking scale.
  • the technical route for rational modeling of on-street parking is aimed at minimizing the comprehensive cost of the transportation system, and achieving the summation of the driver's parking cost and the running cost of the vehicle.
  • the model of reasonable scale of on-street parking is:
  • Max-- of the P can set the maximum number of berths in the road.
  • Step 335 design a model algorithm
  • the rational scale model of on-street parking is devoted to solving the on-street parking scale when the total system cost is the smallest, which is a nonlinear programming problem with univariate constraints. If from a point inside the feasible domain Starting, iteratively according to the unconstrained minimization method, the step size should be properly controlled when performing one-dimensional search, so that the iteration point exceeds the R0 limit, then the barrier factor rk is gradually reduced, ie r1>r2>-- ->rb>--->0, the role of the obstacles is getting smaller and smaller, so the solution is found. It also gradually approaches the minimal solution of the original function.
  • the iterative steps of the interior point method are as follows:
  • Step 340 Plan urban road parking design
  • the technical route for setting up urban on-street parking belts mainly includes the following five aspects:
  • the 2-way parking zone setting has the lowest total cost of transportation and vehicle parking.
  • road conditions and traffic conditions including road section width and road cross section (number of motor vehicles, isolation of aircraft and non-motor vehicle lanes, etc.); traffic conditions include Traffic on motor vehicles, non-motor vehicles and pedestrians. If the road and traffic conditions do not meet the set of on-street parking belts, the road needs to be rebuilt; if the road is difficult to renovate or if it is difficult to meet the requirements even after the renovation, it indicates that the road section is not suitable for setting the on-street parking belt or need to re-select other the way.
  • FIG. 6 is a schematic structural diagram of a real-time release on-street parking service index system according to an embodiment of the present application.
  • the real-time release on-street parking service index system of the embodiment of the present application includes a system front-end monitoring module, a system background service module, a system data analysis and mining service index module, and an on-street parking service index release and sharing module.
  • the system front-end monitoring module mainly includes the front-end information collection terminal such as the underground magnetic parking coil detector, wireless radio frequency communication and video monitoring, and completes the task of collecting the information of the parking space usage status of the road.
  • the physical structure of the system front-end monitoring module of the real-time release on-street parking service index system of the embodiment of the present application is shown in FIG. 7 .
  • the system background service module is used to construct the on-street parking management service index platform to realize the use of on-street parking spaces, road parking service error correction, transaction processing and clearing settlement, parking user management service inspection, information processing report generation and analysis. , forecasting / forecasting / early warning method visualization, on-street parking data storage and sharing, system operation and maintenance and other functions.
  • the structure of the information processing flow of the real-time announcement of the on-street parking service index system in the embodiment of the present application is shown in FIG. 8 .
  • the system data analysis and mining service index module is used to complete system operation monitoring, T-GIS electronic map accurate positioning and matching, on-street parking space data analysis, automatic generation of parking space usage report, financial statement, equipment report, customer service report, user report.
  • Such statistical analysis lays the foundation for the in-depth mining of traffic big data and the deep learning of artificial intelligence, and realizes the management functions such as personnel management, patrol track of law enforcement personnel, illegal handling, accurate positioning of problem parking spaces, and scheduling of integrated mobile phone cluster terminals.
  • the real-time release of the on-street parking service index system interface of the embodiment of the present application is shown in FIG. 9 .
  • the visual query of the real-time release on-street parking service index system in the embodiment of the present application is shown in FIG. 10
  • the real-time release of the embodiment of the present application is shown in FIG.
  • the distribution of the radio frequency communication base station of the on-street parking service index system is shown in FIG. 11 .
  • the distribution of the law enforcement of the in-route parking service index system in the real-time release of the embodiment of the present application is shown in FIG. 12 .
  • the on-street parking service index release and sharing module is used to establish the information release and sharing environment for the on-street parking service index system in real time.
  • the analysis and excavation of the urban on-street parking service index based on the on-street parking management service index platform is carried out.
  • Through the portal website, the visualization results of the real number of on-street parking services are released and shared.
  • the method and system for real-time release of the on-street parking service index in the embodiment of the present invention can save the parking time and parking cost of parking in the city road, improve the effectiveness and convenience of the on-street parking service, and can directly generate the direct benefit of the parking industry, and It can generate indirect benefits of parking services; it can promote the application development of new technologies, new products and new models in urban on-street parking industry by constructing methods and systems for real-time release of on-street parking service index, and realize the value-added of urban road parking information. Services and integrated services generate the commercial and economic benefits of the industrial chain in the on-street parking sector.
  • the total population of Shenzhen has exceeded 21 million, and the number of cars has exceeded 3.22 million.
  • the demand for motorized travel increased.
  • the total daily travel volume of the city was 44.43 million, of which the total number of motorized trips was 21.33 million.
  • the city's motorized travel includes motorized travel for residents and motorized travel for migrants. Among them, the city's residents have a daily average of 19.1 million motorized trips, and the floating population has a daily average of 2.23 million motor trips.
  • the daily average motorized travel volume of residents and floating population in the city accounted for 89.5% and 10.5% of the total daily motorized travel of the city.
  • the occupancy rate of parking berths in urban roads has increased, and parking resources have been used more efficiently.
  • Luohu District has the highest occupancy rate of parking berths, reaching 61.3%. Not only has the parking difficulty problem been effectively alleviated, but the urban road network traffic flow speed has also been greatly improved.
  • Traffic congestion and shared parking environment real-time release of on-street parking service index method and system for the characteristics of social public service of road parking charge management, comprehensive use of traffic big data, artificial intelligence, radio frequency communication, mobile phone cluster communication technology to achieve urban roads
  • the online monitoring mode of the internal parking berth has created a demonstration mode of on-street parking for the Ministry of Housing and Urban-Rural Development of the Ministry of Housing and Urban-Rural Development with accurate judgment, convenient and convenient, reasonable cost and effective law enforcement.

Abstract

本申请涉及智能交通技术领域，特别涉及一种实时发布路内停车服务指数方法及系统。本申请的实时发布路内停车服务指数方法包括：步骤a：建立路内停车设置的车速阻滞模型；步骤b：分析路内停车带设置后机动车辆延误情况；步骤c：选择路内停车带合理设置规模；步骤d：规划城市路内停车设计。本申请可以节省城市路内停车的停车时间与停车成本，提高路内停车服务的实效性与便捷性，既可以产生停车产业的直接效益，又可以产生停车服务的间接效益；通过构建实时发布路内停车服务指数的方法与系统，带动城市路内停车行业对新技术、新产品、新模式的应用发展，实现城市路内停车信息的增值服务与综合服务，产生路内停车领域产业链的商业价值与经济效益。

Description

一种实时发布路内停车服务指数方法及系统 技术领域
本申请涉及智能交通技术领域，特别涉及一种实时发布路内停车服务指数方法及系统。
背景技术
中国已进入新型城镇化建设与发展时期，国务院在2017年2月3日发布了《“十三五”现代综合交通运输体系发展规划》，进一步明确交通运输是国民经济中基础性、先导性、战略性产业，是重要的服务性行业；在有关“交通运输智能化重点工程”内容中提出建设“新一代国家交通控制网示范工程”。当前，中国大城市小汽车与停车位的比例约为1∶0.8，中小城市约为1∶0.5，而发达国家约为1∶1.3，城市停车位比例严重偏低，保守估计中国停车位缺口超过5000万个。深圳市停车位缺口200万个，在城市交通持续拥挤的环境下，政府鼓励机关、企事业单位及路内/路外停车环境错时开放停车位，也鼓励个人把自己不用时的车位拿出来，给他人使用，即所谓的“共享停车”，最大化挖掘路侧停车资源的潜在价值。
路侧停车最直观的反映了城市交通管理水平，世界上绝大多数城市都将路侧停车列为优先发展重点之一。由于受到城市用地资源的限制，静态交通的需求不可能全部通过建设路外停车场来满足；同时，城市道路交通网络的路内停车方式因自身的优点，如：停车便利、步行距离短等而受到车辆驾驶人员的普遍欢迎。大量研究成果表明，在城市中心区域交通流中有30％的车辆是寻找停车位、在全市域道路网络交通流中有20％的车辆是在寻找停车位而造成交通的拥堵。为此，通过对城市路内停车设置的车速阻滞模型建模、对路内交通流运 行影响分析、对路内停车带设置规模建模、对路内停车设计方法四个方面的研究，规划设计了城市路内停车系统。
目前，城市路内停车问题较为突出，存在的主要技术缺点包括：
一、缺乏明确的机动车发展政策
目前，仍未采取较为明确的机动车发展政策，机动车增长速度较为迅猛。而由于停车供给未能跟上停车需求的增长速度，预计在未来几年内，停车供需矛盾仍较为突出。实际上，如果没有明确的机动车限制发展政策，城市道路交通拥堵的增长态势也将日益严峻。从欧美等国家的停车发展历程来看，停车政策的实施大致上经历了一个由事后应对向事前诱导的过程。停车政策也不仅是针对停车问题本身，它同时还被作为整个城市规划、交通政策的一部分加以利用。
二、路内停车泊位需求特征缺乏认识，在泊位设置方面缺乏有针对性的对策
对于泊位需求特征相关的数据仍是通过较为粗放式的统计方式获取，对于不同区域、不同用地类型、不同时段和不同停车目的等详细的、动态的停车特征仍缺乏相应的统计手段。学校、商圈、居住区、大型公共活动场所等居民出行和吸引特征肯定存在较大差异，这些特征区域也将反映对差异化的停车需求。另外，对于不同路段的泊位停放周转率(国家规范一般取7～9车次/日)的测算，也存在较大的误差，而这一指标是直接评价和预测停车泊位需求的关键因素。此外，不同时段的需求特征，包括高峰时段和非高峰时段，日间和夜间的停车需求也需区分对待。
三、停车秩序混乱，泊位设置缺乏统筹和规划，停车梯度价格难以发挥作用
虽然路内停车泊位大多设置在支路、次干路上，但是影响交通微循环系统作用的发挥；现有行人通道、非机动车道被泊位挤占的现象较多；由于路内泊 位的设置，规划的慢行交通通道也难以落实；往往在交叉口、公交车站附近设置路内泊位，影响交通安全。居民区集中区域的路内停车，显然是对附近居民的刚性停车需求进行收费；而在商业集中区域的路内停车价格相对其他区域并不产生明显的阶梯效应，有些只是将这部分停车需求疏导到路外停车场内，并未从根本上减少进入这些区域的人群对小汽车选择使用，造成泊位周转率不高。
四、停车泊位设置形式单一，不能满足多样化停车目的需求，泊位利用率较低
停车和泊车的概念是不同的。停车是指驾驶员不离车，为乘客或货物上下车做短暂停留；泊车是指驾驶员熄火离车时间较长甚至过夜。因此，指示标识应区分多种停车形式，如“禁停/禁泊”、“禁泊不禁停”、“上半月禁泊或下半月禁泊”等。缺乏换乘停车设施。在停车换乘设施方面存在很大缺口，城市中心区域外围居民若通过小汽车接驳进城的地铁，缺乏相应的停车设施。围绕地铁站点周边设施的非机动车停车设施也存在较大缺口，这部分非机动车停车设施也较为简陋，缺乏遮阳、挡雨设施，这大大降低了居民选择非机动车来解决“最后一公里”问题的动力。
五、缺乏差别化的停车管理对策，虽然已在价格方面实施了差异化调控，停车管理手段较为单一
只是根据不同的区域、不同道路等级来制定停车需求调控的差异化管理对策，并据此制定停车价格。实际上，如果即使只是考虑停车需求调控，也难以发挥实际作用，主要原因为：一是泊位控制需求的方案难以落实；二是价格调控需求的方案亦难以落实(价格方案仅对弹性需求有效，而目前的价格方案仅对CBD等购物娱乐性的停车需求产生部分影响。)此外具有根本性差异的停车需求应区分对待，如居民区的停车需求和CBD区域的停车需求采用不同的管理对策，而不是单纯采取价格调控的手段。城市在居民区附近的道路实施居民停车许可制度，保障居民的基本停车需求。许可证通常根据居民的类别分为常驻居民、居民访客、暂住居民等多种形式。
六、建设和管理路内停车泊位部门职能缺乏统筹协调
停车设施建设和管理长期存在市级层面，经费管理融不进区级财税体系，形成了条与块的分离。而在实施停车设施改革调整后，管理体制上形成市级层面主要实施业务指导，区级为建设和管理主体的模式，各区成为停车设施建设和管理的主体。部分城市的机动车设施管理工作由市公安局移交市城管局(道路执法权仍然在交管局)。造成虽然区一级的停车管理机构具有尽可能增加泊位供给的动力。为保障道路资源的网络化运行和监控，必须在市一级进行统一规划和建设管理。红线宽度内的资源，应由城市规划部门进行统筹规划，但是经费管理需进入区级财税。
发明内容
本申请提供了一种实时发布路内停车服务指数方法及系统，旨在至少在一定程度上解决现有技术中的上述技术问题之一。
为了解决上述问题，本申请提供了如下技术方案：一种实时发布路内停车服务指数方法，包括：
步骤a：建立路内停车设置的车速阻滞模型；
步骤b：分析路内停车带设置后机动车辆延误情况；
步骤c：选择路内停车带合理设置规模；
步骤d：规划城市路内停车设计。
本申请实施例采取的技术方案还包括：所述步骤a前还包括：建立路内停车服务指数指标体系，为路内停车的服务水平与服务质量的评估提供科学依据。
本申请实施例采取的技术方案还包括：所述步骤a具体包括：建立路段车速基本模型；建立路内停车带的摩擦效应修正模型；建立路内停车带的阻滞效应修正模型，其中，所述摩擦效应修正后的路段车速模型为：
Figure PCTCN2017117094-appb-000001
ki--基于空间障碍率影响斜率参数；
所述摩擦效应与阻滞效应后的修正模型为：
Figure PCTCN2017117094-appb-000002
式中：k2--基于时间障碍率影响的待标定参数。
本申请实施例采取的技术方案还包括：所述步骤b具体包括：在机动车速阻滞模型建立的基础上，将摩擦效应和阻滞效应作为整体分析路内停车对路段机动车流的干扰，建立相应的理论模型，对路内停车设置后对路段交通流影响进行分析。
本申请实施例采取的技术方案还包括：所述建立相应的理论模型包括：减速-加速延误模型、跟驰延误模型、离散流情况下的跟驰延误模型、连续流情况下的跟驰延误模型、总延误模型建立与车辆延误模型。
本申请实施例采取的技术方案还包括：所述步骤c具体包括：设置车辆停放者行为选择模型；设置车辆停放者成本模型；设置路段出行者出行成本模型；选择路内停车带合理规模；设计模型算法。
本申请实施例采取的技术方案还包括：所述设计的模型算法具体包括：
步骤11：取初始步长ri＞0，允许误差e＞0；
步骤12：找出一可行内点X(0)∈R0，并且令k＝1；
步骤13：构造障碍函数，障碍项可采用导数函数：
Figure PCTCN2017117094-appb-000003
或对数函数形式：
Figure PCTCN2017117094-appb-000004
步骤14：以
Figure PCTCN2017117094-appb-000005
为初始点，对障碍函数进行无约束极小化(在R0内)：
Figure PCTCN2017117094-appb-000006
步骤15：检验是否满足收敛准则：
Figure PCTCN2017117094-appb-000007
或
Figure PCTCN2017117094-appb-000008
步骤16：如满足上述准则，则以X(k)为原问题的近似极小解Xmin；否则，取rk+1＜rk(取rk+1＝rk/10或rk/5)，令k＝k+1，转向步骤13继续进行迭代；
步骤17：考虑到路内停车带位置在城市交通网络拥挤影响因素停车成本增加Y(t)＞0；
步骤18：考虑到路内外停车位共享模式减少的路内停车成本G(t)＞0。
本申请实施例采取的技术方案还包括：所述步骤d包括：选择需要设置路内停车的路段，选择过程要根据道路交通条件与交通量状况对路段能否设置路内停车带做出初步判断；确定路内停车的设计目标：对设置条件进行分析；研究路内停车带合理位置的选择，分析路内停车带与信号交叉口和建筑物出入口及人行横道的间距关系，以及受地形条件及特殊交通环境的限制；对路内停车带泊位的设计方法及其适用性进行研究，并在此基础上考察路内停车带的设置是否满足设计目标，如果不满足，则还需要重新设计路内停车带。
本申请实施例采取的另一技术方案为：一种实时发布路内停车服务指数系统，所述实时发布路内停车服务指数系统包括系统前端监测模块、系统后台服 务模块、系统数据分析与挖掘服务指数模块、路内停车服务指数发布与共享模块，所述系统前端监测模块用于完成路内停车车位使用状况信息的采集任务，所述系统后台服务模块用于构建路内停车管理服务指数平台，实现路内停车车位使用状况、路内停车服务纠错、交易处理与清分结算、停车用户管理服务巡检、信息处理报表生成与分析、预警方式可视化、路内停车数据存储与共享和/或系统运行维护，系统数据分析与挖掘服务指数模块用于完成系统运行监控、T-GIS电子地图精准定位匹配、路内停车车位数据分析和/或自动生成车位使用报表，所述路内停车服务指数发布与共享模块用于实时发布路内停车服务指数系统的信息发布与共享环境建立，实现路内停车服务实数的可视化成果发布与共享。
本申请实施例采取的技术方案还包括：所述系统前端监测模块包括路内停车车位地磁线圈检测器、无线射频通信、视频监控等前端信息采集终端。
相对于现有技术，本申请实施例产生的有益效果在于：本申请实施例的实时路内停车服务指数方法及系统具有“引入交通拥挤与共享停车环境要素的服务指数模式、设计实时发布路内停车服务指数体系、建立实时发布路内停车服务指数方法、开发了实时发布路内停车服务指数系统”整体解决路内停车服务指数评价的优点；本申请实施例的实时路内停车服务指数方法及系统紧密跟踪城市路内停车服务核心问题做为切入点；是在交通大数据时代，对传统调查问卷式评价路内停车服务指数发布的革命性挑战；它克服了传统问卷式评价路内停车的数据静态、周期较长、单一片面、统计繁琐等弊端，通过城市交通大数据路内停车的建模分析与停车行为关联性研究，实时动态地面向政府部门、行业企业、公众出行实时发布路内停车系统运行状态与演变态势，具有重要的商业价值与社会价值。
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图1是本申请第一实施例的实时发布路内停车服务指数方法的流程图；
图2是本申请第一实施例的实时发布路内停车服务指数方法的结构框图；
图3是本申请第二实施例的实时发布路内停车服务指数方法的流程图；
图4是本申请第三实施例的实时发布路内停车服务指数方法的流程图；
图5是城市道路网络路内停车规划与设置流程图；
图6是本申请实施例的实时发布路内停车服务指数系统的结构示意图；
图7是本申请实施例的实时发布路内停车服务指数系统的系统前端监测模块物理结构图；
图8是本申请实施例的实时发布路内停车服务指数系统信息处理流程结构图；
图9是本申请实施例的实时发布路内停车服务指数系统界面图；
图10是本申请实施例的实时发布路内停车服务指数系统可视化查询界面图；
图11是本申请实施例的实时发布路内停车服务指数系统无线射频通信基站分布；
图12是本申请实施例的实时发布路内停车服务指数系统巡检人员执法分布图。
具体实施方式
为了使本发明的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本发明进行进一步详细说明。应当理解，此处所描述的具体实施例仅用以解释本发明，并不用于限定本发明。
请参阅图1和图2，图1是本申请第一实施例的实时发布路内停车服务指 数方法的流程图，图2是本申请第一实施例的实时发布路内停车服务指数方法的结构框图。本申请第一实施例的实时发布路内停车服务指数方法包括以下步骤：
步骤110：量化解析路内停车特征；
在步骤110中，路内停车特性量化是道路交通停车行为的集聚效果与停车供应设施利用程度的体现，反映了城市停车的主要特征、停车设施实用情况、停车供需关系。路内停车特性量化是停车设施规划和评价的主要依据，分析路内停车特性有助于进行城市停车设施规划、制定停车政策与管理措施、调控城市停车供需结构、优化城市道路交通流。
路内停车特征包括以下内容：
路内停车目的结构
路内停车目的结构是指停车者的出行目的，如上班、公务、装卸货物、购物、文化娱乐、接送客人、回家、餐饮等，停车目的在一定程度上决定了路内停车者的行为。路内停车设施规划与停车管理措施的制定需要考虑不同城市区域地理位置、路内停车位与周边社区车位共享等，停车目的结构会对停车泊位供需调控和停车管理政策产生影响。
平均停车时间
一定时间路段内所有车辆的路内停车时间与实际停车量之比的平均值，是反映城市路内停车设施使用情况的重要指标。停车时间的长短与城市规模、城市不同功能的区域、路内停车设施的类型、路内停车位共享、停车目的密切相关。不同目的的停车者对停车时间要求存在差异，目前尚未采取措施限制停车时间，导致路内停车时间偏长，使用效率较低，城市中心区域交通拥堵现象较为严重。
高峰停放指数
高峰停放指数是指高峰时段累计停放车辆数与停车设施容量之比，它反映的是高峰时段停车设施的拥挤程度，同时也是确定停车设施规模的重要依据。
泊位利用率
泊位利用率是指在一定时段内平均每个泊位停车占用时间与总停泊位时间之比，反映停车泊位的时间利用效率，表达了停车设施的拥挤程度。平均泊位利用率越高，泊位的时间利用效率也就越高，反映了泊位的时间利用效率与服务水平的差异。
泊位周转率
泊位周转率是指在一定的时间内每个停车泊位平均停放车辆的次数，常用在一天内的累计停放车辆数与停车设施容量之比来表示，反映的是停车设施泊位的空间利用效率。城市不同区域、不同共享停车位、不同停车设施的泊位周转率有所差异，城市中心区域的泊位周转率高于城市外围区域。
步骤120：分析路内停车者的停车行为；
在城市道路交通系统中，受自身条件与外界条件的影响，不同的停车者在选择停车服务时会有不同的行为，不同区域的停车行为也有很大的差异，停车行为人在一定的交通环境下还表现出相应的特性。停车行为与特征体现了停车的根本特点，是分析城市停车供需关系，解析城市停车矛盾的基本依据，分析和掌握路内停车行为与特性是城市路内停车规划制定与路内停车政策法律法规的重要基础。
停车者在选择停车服务时，供选对象往往不止一个，可以选择路内停车，也可以选择路外停车，停车综合考虑各种因素是最终选择适合自己的停车服务设施。一般情况停车者在评估停车设施时主要受经济因素、使用效率、使用习惯、环境因素、停车者自身特性、车辆特性的影响。
路内停车者的停车行为具体包括：
1、经济因素与停车行为
从经济角度来看，停车者选择停车服务的过程是一种消费过程，停车者付出一定的代价来换取与之等价的停车服务，停车者的选择过程也遵循消费者的经济行为规律。停车收费对停车行为影响严重，停车人员类型对停车行为影响也有很大差异，停车可达时间对停车费用的折减，道路交通拥堵指数价格因素直接影响停车者的行为，停车位的共享状况也会使停车成本降低。
2、使用习惯与停车行为
停车习惯是在个人偏好、社会环境、停车设施的供应特点等因素的影响下形成的，不同类型的城市规模其停车习惯有较大的差异，如停车时间长短对停车设施选择的心理差异、大/中/小城市对步行距离要求的差异等。
3、环境因素与停车行为
人文环境对停车行为有一定的影响，如不同类型的住宅对应于不同层次的消费群体，居住区档次越高，住宅户均车辆拥有率和对停车服务的质量要求越高，停车者更注重停车的安全性，而对经济因素不敏感；低档次住宅区家庭收入相对较低，停车服务的选择除了安全性外，停车费用的影响较大。
4、车辆特点与停车行为
车辆特点直接影响停车行为，主要表现在本地车与外地车、公车与私车、新车与旧车、车辆价格的高低等所体现出来的停车行为差异。如外地车辆对停车设施的位置、收费等情况不熟悉，不愿意为寻找、选择停车设施而过多浪费时间，经常以距离目的地最近为原则或按习惯选择停车设施；本地车辆对停车的位置、收费等情况较为熟悉，停车者会综合考虑各方面的影响因素做出选择，通常以服务效用最大化为原则选择停车设施。
步骤130：量化分析路内停车设施与停车行为；
随着城市机动车保有量的迅速增长，停车问题日益突出，停车难成为城市 交通日益关心的问题，解决停车难问题的重要途径之一就是运用高科技手段，提高停车位的周转率，而每辆车的停车时间长短直接关系到停车位的使用效率。需要分析研究停车者对于停车时间的选择影响因素，为利用政策因素(如停车价格等)调节停车时间长度、提高停车位的周转效率。采用离散选择Logistic模型技术，建立路内停车时间与停车行为之间的关系模型，多项式Logistic回归分析用于解决多项分类变量与影响因素之间关系，是停车行为离散选择模型技术的深化应用。城市路内停车时间与停车目的，停车价格，停车费用支付者之间有明显的关系，将这些变量代入Logistic模型，建立路内停车行为模型，完成路内停车设施与路内停车行为的关系分析。
步骤130具体包括：
步骤131：量化分析社会公共路内停车行为影响因素；
①社会公共停车行为主要影响因素分析
社会公共停车环境作为弥补配建不足的停车场所，可以分为弥补办公配建不足、弥补商业配建不足、弥补医院配建不足等停车环境，停车时间的分布范围广、根据有关分析将停车时间与各个停车行为指标进行相关分析，找出停车时间与停车目的、停车价格、停车费用支付者之间的关联性，从而建立停车行为模型。
②路内停车时间影响因素的量化分析
选取停车时间大于4小时的概率P3n作为P1n和P2n的参照组，建立停车时间选择模型。因此，停车时间为因变量，将停车目的、停车费用支付者作为分类变量，停车价格作为连续变量代入模型，得到结果如下：
Figure PCTCN2017117094-appb-000009
Figure PCTCN2017117094-appb-000010
式中：Costin--第n个停车者选择时长i的停车位收费价格；
Userin--第n个停车者停车费用支付者哑元变量；
Goalin--第n个停车者停车目的哑元变量；
θk--参数。
步骤132：建立商业路内停车行为模型；
①商业停车行为主要影响因素分析
商业停车的主要停车目的是为娱乐休闲，停车费用支付者主要为个人支付，将停车时间与各个停车行为指标进行相关分析，得出停车时间与停车目的、停车价格有明显的关系，在不同费用支付者的条件下，找出影响停车时间的主要因素。
②停车时间影响因素量化分析
选取停车时间大于4小时的概率P3n作为P1n和P2n的参照组，建立停车时间选择模型。因此，停车时间为因变量，将停车目的作为分类变量，停车价格作为连续变量代入模型，得到结果如下：
Figure PCTCN2017117094-appb-000011
Figure PCTCN2017117094-appb-000012
式中：Costin--第n个停车者选择时长i的停车位收费价格；
Goalin--第n个停车者停车目的哑元变量；
θk--参数。
步骤133：建立办公路内停车行为模型；
①办公路内停车行为主要影响因素分析
办公停车的主要停车目的是为工作，停车费用支付者主要为单位支付，个人支付也有一定比例。将停车时间与各个停车行为指标进行相关分析，得出停 车时间与停车目的、停车价格有明显的关系，在不同费用支付者的条件下，找出影响停车时间的主要因素。
②办公停车时间影响因素量化分析
选取停车时间大于6小时的概率P3n作为P1n和P2n的参照组，建立停车时间选择模型。因此，停车时间为因变量，将停车目的作为分类变量，停车价格作为连续变量代入模型，得到结果如下：
Figure PCTCN2017117094-appb-000013
Figure PCTCN2017117094-appb-000014
式中：Costin--第n个停车者选择时长i的停车位收费价格；
Goalin--第n个停车者停车目的哑元变量；
θk--参数。
步骤140：路内停车需求预测建模。
当车辆驾驶者因活动需要产生出行而有空间上的移动，并在出行终点需要空间和时间停放交通工具，由此所需要的停车空间与时间即成为停车需求，表示为车位/小时。根据停车时间来划分，停车需求有日间停车需求及夜间停车需求，日间停车需求是为了满足各种社会、经济活动的目的所引发的需求，主要表现为社会停车需求，城市路内停车位使用率较高，也是一种交通运输行为的派生需求；夜间停车需求是因车辆保有及夜间活动引起的停车需求，主要表现为基本停车需求，因为大部分夜间停车需求是为居民或单位车辆夜间停放服务的，夜间停车需求的发生地点比较固定，其出行目的也比较单纯，故一般较日间停车需求容易估算，城市路外停车位使用率较高；综合路内与路外停车位的使用频次与周期关系，建立城市路内与路外停车位的互补性共享车位，提高城市路内与路外停车位共享的使用率。
路内停车需求影响因素：车辆的停放是城市的社会、经济、人文、交通发展到一定程度的产物，城市路内停车需求量受到多方面的影响，主要包括以下内容：
①规划区域内土地利用及未来发展状况；
②规划区域的人口、就业、机动车保有水平及社会经济发展状况；
③城市发展战略、交通发展策略、交通整体规划以及停车管理水平；
④规划区域内的交通体系构成及运行状况；
⑤城市交通政策、地理、气象条件、风俗习惯、文化等都会对停车需求产生影响。
路内停车需求预测建模方法具体包括
步骤141：建立停车生成率模型；
停车生成率(Parking Generation Rates)是指单位土地利用指标所需的停车泊位数。停车生成率模型是建立在土地利用性质与停车需求生成率之间关系的基础上，其技术路线是将区域内各种不同土地利用性质的地块都看作为停车吸引源，而区域总的停车需求量等于这些单个地块吸引量之和。停车生成率模型如下：
Figure PCTCN2017117094-appb-000015
式中：Pd--第d年高峰时间停车需求量(泊位数)；
Rdj--第d年j类用地单位停车需求生成率；
Ldj--第d年j类土地使用量(面积或员工数)。
步骤142：建立用地与交通影响分析模型；
用地与交通影响分析模型是建立在城市停车需求与该区域的经济活动特性和交通特性密切相关的基础上，通过对停车特征调查和土地利用性质调查， 从机动车保有量、土地利用等现状及其变化趋势入手，确定它们与停车需求的关系，进而分析现状停车需求及预测未来的停车需求。该模型是停车生成率模型的扩展，既具备了生成率模型的特点，有将停车生成率与道路交通量相结合，较好地兼顾了停车与土地利用和交通之间的关系。其模型如下：
Figure PCTCN2017117094-appb-000016
式中：P(t)--规划区域内t年度的日停车需求量(标准泊位)；
F(xi)--停车需求的地区特征函数；
xi--第i区域的土地利用规模，可用相应不同类型的用地面积表示，也可以用响应不同类型用地的从业人数来表示；
f(γq)--日停车需求的交通影响函数；
γq--规划区域内交通量的年平均增长率(％)。
步骤143：建立用地分析模型；
用地分析模型又称为商业用地停车分析模型，是基于停车需求与用地性质、雇员数量之间的关系来对以商业为主的地区，进行未来规划年的停车需求预测。其基本假设为：一个以商业为主的地区，长时间停车需求是由雇员上班出行引起的，而短时间停车需求是由在该地区进行的商业活动引起的。具体预测模型为：
Figure PCTCN2017117094-appb-000017
式中：di--第i区域高峰停车需求(泊位数)；
AL--长时间停车总累计停车数；
AS--短时间停车总累计停车数；
ei--第i区域雇员数；
ej--第j区域雇员数；
Fi--第i区域零售及服务业建筑面积(平方米)；
Fj--第j区域零售及服务业建筑面积(平方米)；
J--小区数。
步骤144：建立出行吸引模型；
停车需求的生成与地区的经济社会强度有关，而社会经济强度又与该地区吸引的出行车次有密切关系。出行吸引模型的原理是建立高峰小时停车需求泊位数与区域机动车出行吸引量之间的关系，建模的基础条件是开展城市综合交通规划调查，根据各交通小区的出行分布模型和各小区的停放吸引量建立数学模型，由此推算出获得停车车次的预测数据。停车需求模型如下：
Pi＝[Ni+(Di1·f(s)-Oi1)]+(Di2·f(s)-Oi2)
式中：Pi--第i小区高峰停车需求量(泊位数)；
Ni--第i小区夜间停车辆(泊位)；
Di1--第i小区高峰时段前累计交通吸引量(车次)；
Oi1--第i小区高峰时段前累计交通发生量(车次)；
Di2--第i小区高峰时段末累计交通吸引量(车次)；
Oi2--第i小区高峰时段末累计交通发生量(车次)；
f(s)--机动车停车生成率。
步骤145：建立多元回归分析预测模型；
在研究城市路内停车需求的本质与因果关系中，可以发现停车需求与城市经济活动、土地使用等多因素相关。回归分析模型是根据若干年相关变量的历史资料，用回归分析计算出其回归系数值，并进行统计检验。同时，通过线性趋势预测方法预测各影响因素的未来值，代入回归公式，即可预测未来停车需求。具体预测模型为：
Pdi＝K0+K1(EPdi)+K2(POdi)+K3(FAdi)+K4(DUdi)+K5(RSdi)+K6(AOdi)+…
式中：Pdi--d年第i区高峰时间停车需求量(泊位数)；
EPdi--d年第i区就业岗位数；
POdi--d年第i区人口数；
FAdi--d年第i区建筑面积；
DUdi--d年第i区企业数；
RSdi--d年第i区零售服务业数；
AOdi--d年第i区小汽车保有数；
Ki--回归系数，i＝1，2，3，4，5，6，…。
步骤146：建立交通量--停车需求模型。
任何地区的停车需求必然是到达该地区行驶车辆被吸引的结果，停车需求泊位数为通过该地区流量的某一百分比。如果该地区用地功能较为均衡、稳定，则建模的预测较为可靠。具体模型为：
lgPj＝A+BlgVj
式中：Pj--j分区高峰小时停车需求量(标准车车次)；
Vj--j分区高峰小时交通流量；
A，B--回归系数。
交通量--停车需求模型的预测方法简单，思路明确，适用于用地功能均衡、稳定地区的短期预测。该模型忽略了不同种类车辆停车生成率的偏差，不能反映因交通政策或控制手段引发的交通流组成的变化对停车需求的影响；而且利用交通量--停车需求模型进行预测，无法具体得到区域内每一土地使用的停车设施需求量，所以该模型仅作为验证其他预测模型预测结果的方法。
请参阅图3，是本申请第二实施例的实时发布路内停车服务指数方法的流程图。本申请第二实施例的实时发布路内停车服务指数方法包括以下步骤：
步骤210：建立路内停车服务指数指标体系；
在步骤210中，交通拥挤与共享停车环境的实时发布路内停车服务指数方法是根据路内停车的基本特征，建立相关服务指数的指标体系，为路内停车的服务水平与服务质量的评估提供科学依据，具体包括以下指标：
(1)停车供应：是指一定的路内停车区域停放场地可能提供最大停放车位数，停放供应的计量在调查中用实际可停放数表示。
(2)停车需求：指给定停车区域内特定时间间隔的停放吸引量，用代表性目的高峰期间停放数表示。
(3)停车设施容量：指给定停车区域或停车场有效面积上可同时合法停放车辆的最大泊位数，通常用车位数表示。
(4)停车目的：是指出行活动中有目的的路边停放，停车目的与通勤通学、购物娱乐、外出办事等出行目的相一致。
(5)步行距离：是指停车存放后至出行目的地的实际步行距离，通常以米为单位；可反映停车设施布局对停放车辆的方便程度，也是路内停车系统规划及停车信息诱导发布的重要控制因素之一。
(6)累计停车量：是指一定时间内停车设施累计停放的车辆数。
(7)停放时间：是指车辆在路内停车位的实际停放时间，它是衡量停车带交通负荷与周转效率的基本指标之一，其分布与停放目的、停放点土地使用等因素有关。
(8)停放饱和度：是指某一时刻实际停放的车辆数与停车带设施容量之比，反映停车设施的拥挤程度。高峰时段停车数量与停车设施容量之比称为高峰停放饱和度。
(9)泊位周转率：是指单位停车泊位在工作时间内的平均停车次数，通过车辆占用停车泊位的频繁程度来反映停车泊位的空间利用效率。
(10)泊位利用率：是指工作时间内平均每个停车泊位实际占用的时间与总工作时间之比，反映停车泊位的时间利用效率。
(11)延停车数：是指一定时间间隔，调查点或区域内累计停放次数，即各个间隔观测时段获得的延停车辆数之和，单位为辆次。
(12)平均延停时间：表示全部实际停放车辆的平均停放时间，平均延停时间即为总延停时间除以实际停放车辆数。
(13)停车密度：是指停车负荷的基本度量单位，它既表示停放吸引量大小随时间段变化的程度，通常为高峰时段停放密度最高；又表示其空间分布，在不同吸引点停车吸引量的大小程度。
步骤220：分析城市路段设置路内停车对车流影响；
在步骤220中，城市路段设置路内停车对车流影响主要包括两个部分：
①迫使非机动车行驶轨迹向机动车道偏移或侵占机动车道，使得机动车车速变缓形成机动车与非机动车混行状态，即所谓的摩擦效应。
②路内停放车辆的驶入和驶出可能阻断路内交通流，特别是道路交通量较大时，车辆的驶入、驶出往往不等完成可穿越的车流间隙，而是强行穿越，给路段上车辆带来很大干扰，甚至造成交通阻塞，即所谓的阻滞效应。
根据Blunden交通量有关路阻函数的理论特性：当流量充分小时，行程时间接近于平均零流量行程时间；在流量远小于道路的通行能力时，流量的缓慢变化，导致行程时间的缓慢变化；在稳态系统状态下(流量接近道路通行能力时)，行程时间增力很快。
步骤230：建立交通流延误模型；
在不考虑其他交通工具和环境因素作用对路段车流的影响，机动车流在设 置路内停车带前相对平稳，非机动车道由于没有阻挡物，机动车和非机动车相互干扰较少，机动车以正常速度(υf)行驶。当设置路内停车带以后，由于非机动车道有了路内停车带设置，使得非机动车饱和度提高。为了摆脱相互制约，非机动车往往会驶入机动车道。因此，当路段设置路内停车带后，路段车流运行状态可描述为：“以路段正常速度(υf)前进→减速(α′)进入路内停车带→以形成机动车与非机动车混行的速度(υb)前进(υb定义为机与非混行和停车带车辆到达驶出阻滞影响综合作用下的平行行程车速)→加速(α)离开路内停车带→重新以稳定速度(υe)前进”。速度变化直观反映了设置路内停车前后的堵塞状况，延误则最直观地反映了设置前后道路效益损失，是设置路内停车提供最为直接的依据。
步骤240：匹配共享路内停车带与路外停车场；
路内停车带与路外停车场都是公共停车场不可缺少的组成部分，路内停车带的设置地点离出行目的地较近，便利性强，周转率较高，但同时形成路段交通流的活动瓶颈，对其他出行者影响较大；路外停车场的设置地点离出行目的地较远，便利性弱，周转率较低，但对路段其他出行者影响较小。因此，如何寻找路内停车带与路外停车场泊位设置的合理匹配关系，既能保障较好的停车便利性，又能将对路段其他出行者的影响控制在一定的范围内，最求系统总效益的最大化，是路内停车带合理设置规模的重点。
请参阅图4，是本申请第三实施例的实时发布路内停车服务指数方法的流程图。本申请第三实施例的实时发布路内停车服务指数方法包括以下步骤：
步骤310：建立路内停车设置的车速阻滞模型；
在步骤310中，路内停车利用道路空间资源作为停车载体，与路外停车设施相比具有设置灵活简单、建设成本低、占用空间少、方便直接等优点。但是，由于路内停车不仅以道路作为其停放空间，而且作为其驶入与驶出的通道，对路段交通流运行状态的影响也最为直接。基于路段交通负荷水平的路段行驶车 速(或时间)关系模型的建立，有助于调节路内停车带设置后对路段交通流的影响程度。路内停车带的设置主要有两种：停车带在机动车与非机动车混行车道上，该位置主要存放在于道路断面一幅路和二幅路的情况，设置停车带后，对机动车和非机动车都产生影响，应重点分析机动车流产生的交通阻滞和延误；以及停车位设置在非机动车场后，该位置主要存在与道路断面三幅路和四幅路的情况，设置停车场后，主要对非机动车产生影响，在考虑设置条件时，主要从设置后对非机动车道通行能力的影响入手，对路段机动车流的影响较小。
步骤310具体包括：
建立路段车速基本模型；
基于此，路段设置路内停车带后，根据车辆速度与道路流量的基本关系路
阻函数模型对统计数据进行拟合，其形式为：
Figure PCTCN2017117094-appb-000018
式中：υ--路段机动车实际运行速度km/h；
υ0--零流量下的运行车速km/h；
q--机动车实际交通流量veh/h；
c--路段通行能力veh/h；
α，β--无量纲参数；
i--交通运行类变量种类，包括同向机动车、同向非机动车、对向机动车、对向非机动车等。
建立路内停车带的摩擦效应修正模型；
路内停车带对路段交通流的摩擦效应主要通过Rb体现，不同的空间障碍率Rb会对道路动态交通流产生不同的摩擦影响，随着Rb的增大，道路车流之间摩阻增加，道路交通流速会随之下降。考虑摩擦效应修正后的路段车速模型为：
Figure PCTCN2017117094-appb-000019
式中：ki--基于空间障碍率影响斜率参数。
建立路内停车带的阻滞效应修正模型。
路内停车的阻滞效应一方面同步产生摩擦效应，另一方面受路内停车的驶入、驶出过程和停驶方式的影响。因此，这里提到的阻滞效应均是指在摩擦效应基础上的车辆驶入、驶出对路段车流的阻滞。阻滞效应主要通过不同的时间障碍率RT来体现，随着RT的增大，道路交通流速度随之下降。考虑摩擦效应与阻滞效应后的修正模型为：
Figure PCTCN2017117094-appb-000020
式中：k2--基于时间障碍率影响的待标定参数。
步骤320：分析路内停车带设置后机动车辆延误情况；
在步骤320中，在机动车速阻滞模型建立的基础上，考虑不同机动车交通流到达条件下，将摩擦效应和阻滞效应作为一个整体分析路内停车对路段机动车流的干扰，建立相应的理论模型，对路内停车设置后对路段交通流影响进行分析。建立相应的理论模型包括：
减速-加速延误模型
设定某路段车辆正常行驶的平均速度为υf km/h，车辆的平均减速度为α′m/s-2，车辆在路内停车带的跟驰速度为υb km/h，则车辆从正常行驶平均速度υf减速到跟驰速度υb的距离s为：
Figure PCTCN2017117094-appb-000021
车辆从正常行驶平均速度υf减速度到车辆在路内停车带的跟驰速度为υb的减速度时间t1为：
Figure PCTCN2017117094-appb-000022
在无路内停车带干扰时，车辆以正常行驶平均速度驶过减速距离s的时间为：
Figure PCTCN2017117094-appb-000023
则车辆从正常行驶平均速度υf减速度到跟驰速度υb的减速延误为：
Figure PCTCN2017117094-appb-000024
同理，设定某路段车辆的平均速度为αm/s-2，车辆加速度行驶的最终速度为υe，可得到车辆的加速延误dd为：
Figure PCTCN2017117094-appb-000025
跟驰延误模型
对于一条道路，当路内设置路内停车带时，自行车为了超越它前面的自行车，往往会占用机动车道行驶，将使机动车无法具备超越其前面自行车的路宽条件，不得不在自行车后面跟驰行驶，此时的速度大大低于正常的行驶速度，跟驰过程中的行驶时间要多于正常速度通过跟驰路段的行驶时间，从而产生跟驰延误。
当道路中的交通流密度不大，车辆间的相互影响微弱，前后车辆的到达表现为相互独立性，这时交通流的到达具有随机性，可以用概率模型来描述道路某一断面在一定时间间隔内到达的车辆数。当车流密度较大时，车辆间存在着相互约束，前后车辆的到达不是相互独立的，此时交通流具有流体的连续性特征，采用流体力学理论来描述车流运行的状况。
离散流情况下的跟驰延误模型
当道路中的交通流密度不大，车流随机到达情况下，一定时间间隔内到达的车辆数可视为随机变量，用离散型分布来描述此类随机变量。对于车流密度不大，车辆间相互影响微弱的情况，用泊松分布能够较好地描述车辆间的到达。因此，设定交通流到达服从泊松分布。
对于路段上的某一点x0，假设车辆的到达率为λ，Δt时间内到达k辆车的概率Pk(Δt)为：
Figure PCTCN2017117094-appb-000026
因机与非混行干扰而排队的车辆数L，为：L＝E1(tf)-E2(tf)＝(λ-μ)tf；在tf时间内到达点x0的车辆产生排队，根据Little公式，任何排队系统，顾客在系统内平均停留时间等于系统内顾客的平均数除以顾客到达率，即顾客数在系统内停留时间期望值为：
Figure PCTCN2017117094-appb-000027
设路内停车带设置长度为L，在0到tf时间内，因机与非混行造成的跟驰延误df为：
Figure PCTCN2017117094-appb-000028
余此类推，在单位统计时间间隔T时间年内，由于路段内机与非混行造成的跟驰延误D为：
Figure PCTCN2017117094-appb-000029
连续流情况下的跟驰延误模型
当道路交通流中前车与后车的到达不是离散的、相互独立的，而是连续的、相互影响的，此时车辆的到达不能用概率模型进行描述。交通流可以采用流体力学理论进行描述车流的运行状况。
设第一辆车驶完路内停车带所需的时间为tf，车流进入路内停车带后，形成的车队尾部以ω1的速度向后移动，而拥挤车队的头部以υb的速度前进，则拥挤车队的车辆增加率g1为g1＝(υb-ω1)k2；在实间0至tf内，拥挤车辆增加至：Nm＝g1tf＝(υb-ω1)k2tf；设开始进入路内停车带影响区的时间为零时刻，则路内停车带拥挤车辆数随时间t的函数为：
Figure PCTCN2017117094-appb-000030
在时间微段(t，t+Δt)内，可认为拥挤车辆数都等于n(t)，此时每辆车行驶 的距离为υbΔt，此段距离若以车辆正常行驶速度υf行驶，只需用
Figure PCTCN2017117094-appb-000031
时间，因此由于拥挤而延误的时间为：
Figure PCTCN2017117094-appb-000032
n(t)辆车载t到t+Δt内的总延误Δd为：
Figure PCTCN2017117094-appb-000033
在0至tf时段内的跟驰延误Df1为：
Figure PCTCN2017117094-appb-000034
在时间tf至2tf时段内，拥挤车辆数N2又增加至：N2＝(υb-ω1)k2tf-ω1k2tf＝Nm-ω1k2tf；在tf至2tf时段内的跟驰延误Df2为：
Figure PCTCN2017117094-appb-000035
接下来的时段延误，可按上述延误的技术路线余此类推。
在(n-1)tf至ntf时段内，拥挤车辆数Nn又增加至：Nn＝(υb-nω1)k2tf＝Nm-(n-1)ωk2tf；在(n-1)tf至ntf时段内，跟驰延误Dfn为：
Figure PCTCN2017117094-appb-000036
Figure PCTCN2017117094-appb-000037
此时计算0至ntf时段内，总的跟驰延误Dnf为：
Figure PCTCN2017117094-appb-000038
一个统计间隔tt时间内，产生的拥挤车辆数Nmti为：
Figure PCTCN2017117094-appb-000039
由此产生的跟驰延误Dt为：
Figure PCTCN2017117094-appb-000040
Figure PCTCN2017117094-appb-000041
总延误模型建立与车辆延误模型
机动车流受摩擦和阻滞干扰而引起的总延误包括减速延误、跟驰延误、加速延误三个部分，对于交通流为离散情况下，设路段上单位时长的总延误为Dt，离散交通流下单车的跟驰延误为dt，则研究路内停车带影响区域1小时的离散流总延误为：
Figure PCTCN2017117094-appb-000042
式中：λi，μi--车辆的到达率和离开率；
ddi，dai--车辆的减速延误和加速延误；
tt--单位统计时间，取1小时；
dti--单位时间内跟驰延误。
对于交通流为连续流情况下，可得出1小时的总延误为：
Figure PCTCN2017117094-appb-000043
式中：ddi，dai--车辆的减速延误和加速延误；
Nmti--单位统计时间拥挤车辆数；
Dti--单位时间内跟驰延误。
对于交通流为离散时出车均延误为：
Figure PCTCN2017117094-appb-000044
对于交通流为连续流时出车均延误为：
Figure PCTCN2017117094-appb-000045
步骤330：选择路内停车带合理设置规模；
在步骤330中，步骤330具体包括：
步骤331：设置车辆停放者行为选择模型；
在国内大城市现有停车设施服务水平下，高达90％的驾车者首选路内停车带进行停放车辆，同时根据车辆停放特征研究表明，路内停车到达服从伯松分布，被服务的时间即停车时间服从负指数分布，在停车行为选择模型中假设车辆停放者首选路内停车带，当停车场停满时，后来的车辆将另外寻找路外停车场，不会排队等候空位。因此，可以将车辆停放者的行为选择视为伯松分布/负指数分布/N个服务台的损失至排队系统。
假设驾车者的到达服从参数为λ的泊松分布，驾车者的服务时间服从参数为μ的负指数分布，目的地由P内服务台。
路内停车带空闲的概率P(0)：
Figure PCTCN2017117094-appb-000046
因停放车位已满而拒绝停车的概率P(P内)：
Figure PCTCN2017117094-appb-000047
式中：m--计数间隔t内平均到达人数，m＝λt；ρ--路内停车带服务强度，
Figure PCTCN2017117094-appb-000048
单位时间内被拒绝的车辆数Zj：Zj＝λ·P(P内)；式中：P内--路内停车带的泊位规模数。
步骤332：设置车辆停放者成本模型；
对车辆停放者而言，当出行目的地附近路内停车设施没有空闲空位时，短时停车也必须停放在路外停车场，造成停车绕行所产生的时间损失、步行至目的地距离增加以及路内和路外停车收费的差异性等，直接导致了停车者停放成本的变化。因此，定义车辆停放者的成本函数为S(P内)，它包括路外停车与路内停车的停放时间差和停放费用差、以及该路内停车带所处的城市道路网络中拥挤程度影响增加的成本、路内与路外停车位共享所增加收益共四个部分，S(P内)随着路内停车规模的增大而减小。
S(P内)＝Zj(AmT1+f1(t))+Y(t)-G(t)；
式中：Zj--单位时间内被路内停车带拒绝而转向路外停车场的车辆数(辆/小时)；
A--小汽车出行者平均单位时间价值(元/(人·小时))；
m--每辆小汽车平均载客数(人/pcu)；
fl(t)--路外停车与路内停车费用差(元)；
Ti--车辆在路外停放相对路内停放的增加时间(小时)；
Y(t)--该路内停车带所处的城市道路网络中拥挤费增加的成本(元)；
G(t)--路内与路外停车位共享所增加收益(元)。
步骤333：设置路内停车后对动态交通的影响主要体现在减少了道路通行能力，增加了道路的负荷度，从而对其他小汽车出行者的行程速度产生影响，产生了延误，增加了出行成本。定义对其他出行者增加的出行成本函数N(P内)，为该路段其他出行者由于路段停车带产生延误而产生的增加出行成本，N(P内)随着路内停车规模的增大而增大。
N(P内)＝AmDt+f1(t))+Y(t)-G(t)；
式中：Dt--设置路内停车带对路段车流形成的1小时总延误(小时)。
步骤334：选择路内停车带合理规模；
路内停车带的最佳规模也即寻求当系统总成本最小时，路内停车带与路外停车场规模之间合理的匹配关系。随着路内停车带规模增大，停车者的停放成本随着路内停车规模增大而逐渐变小，而非停车的路段其他出行者出行成本随着路内停车带规模增大而逐渐变大，因此对于社会总成本，也即停车者的停放成本和其他非出行者出行成本之和，必然存在一个最小值，对应着最佳的路内停车带规模。
路内停车带合理建模的技术路线是以交通系统综合成本最小为目标，实现驾车者停放成本和车流运行成本的总和优化。基于交通拥堵与共享停车环境的影响要素，路内停车带合理规模的建模模型为：
Figure PCTCN2017117094-appb-000049
式中：P内max--路段可设置路内最大泊位数。
步骤335：设计模型算法；
路内停车合理规模模型致力于求解系统总成本最小时的路内停车规模，属于单变量约束的非线性规划问题。如果从可行域内部的某一点
Figure PCTCN2017117094-appb-000050
出发，按无约束极小化方法进行迭代，在进行一维搜素时要适当控制步长，以免迭代点超出R0界限，则随着障碍因子rk的逐步减小，即r1＞r2＞---＞rb＞---＞0，障碍项所起的作用也越来越小，因而求出的解
Figure PCTCN2017117094-appb-000051
也逐步逼近原函数的极小解。内点法的迭代步骤如下：
1)取初始步长ri＞0，允许误差e＞0；
2)找出一可行内点X(0)∈R0，并且令k＝1；
3)构造障碍函数，障碍项可采用导数函数：
Figure PCTCN2017117094-appb-000052
或对数函数形式：
Figure PCTCN2017117094-appb-000053
4)以
Figure PCTCN2017117094-appb-000054
为初始点，对障碍函数进行无约束极小化(在R0内)：
Figure PCTCN2017117094-appb-000055
5)检验是否满足收敛准则：
Figure PCTCN2017117094-appb-000056
6)如满足上述准则，则以X(k)为原问题的近似极小解Xmin；否则，取rk+1＜rk(取rk+1＝rk/10或rk/5)，令k＝k+1，转向3)继续进行迭代；
7)考虑到路内停车带位置在城市交通网络拥挤影响因素停车成本增加Y(t)＞0；
8)考虑到路内外停车位共享模式减少的路内停车成本G(t)＞0。
步骤340：规划城市路内停车设计；
设置城市路内停车带的技术路线主要包括以下五个方面的内容：
(1)选择需要设置路内停车的路段，选择过程要根据道路交通条件与交通量状况对路段能否设置路内停车带做出初步判断。
(2)确定路内停车的设计目标：
①控制路段车流的饱和度与延误；
②路内停车带设置对交通出行和车辆停放的总成本最小。
(3)对设置条件进行分析，包括道路条件与交通量条件两个方面，其中道路条件包括路段宽度和道路横断面形式(机动车道数、机与非机动车道隔离方式等)；交通量条件包括路段机动车、非机动车和行人的流量。如果道路和交通量条件不满足设置路内停车带，则需要对道路进行改造；如果道路难以改造或即使改造之后还难以满足要求，则表明该路段不适合设置路内停车带或需要重新选择其他道路。
(4)研究路内停车带合理位置的选择，分析路内停车带与信号交叉口和建筑物出入口及人行横道的间距关系，以及受地形条件及特殊交通环境的限制等。
(5)对路内停车带泊位的设计方法及其适用性进行研究，并在此基础上考察路内停车带的设置是否满足设计目标，如果不满足，则还需要重新设计路内停车带。
城市道路网络路内停车规划与设置流程详见图5所示。
请参阅图6，是本申请实施例的实时发布路内停车服务指数系统的结构示意图。本申请实施例的实时发布路内停车服务指数系统包括系统前端监测模块、系统后台服务模块、系统数据分析与挖掘服务指数模块、路内停车服务指数发布与共享模块。
系统前端监测模块主要包括路内停车车位地磁线圈检测器、无线射频通信、视频监控等前端信息采集终端，完成路内停车车位使用状况信息的采集任务。本申请实施例的实时发布路内停车服务指数系统的系统前端监测模块物理结构详见图7所示。
系统后台服务模块用于构建路内停车管理服务指数平台，实现路内停车车位使用状况、路内停车服务纠错、交易处理与清分结算、停车用户管理服务巡检、信息处理报表生成与分析、预测/预报/预警方式可视化、路内停车数据存储与共享、系统运行维护等功能。本申请实施例的实时发布路内停车服务指数系统信息处理流程结构详见图8所示。
系统数据分析与挖掘服务指数模块用于完成系统运行监控、T-GIS电子地图精准定位匹配、路内停车车位数据分析、自动生成车位使用情况报表、财务表报、设备报表、客服报表、用户报表等统计分析，为交通大数据的深入挖掘、人工智能的深度学习奠定基础，实现人员管理、巡检人员执法轨迹回放、违章处理、问题车位处所精准定位、集成手机集群终端的调度等管理职能。
本申请实施例的实时发布路内停车服务指数系统界面详见图9所示，本申请实施例的实时发布路内停车服务指数系统可视化查询详见图10所示，本申请实施例的实时发布路内停车服务指数系统无线射频通信基站分布详见图11所示，本申请实施例的实时发布路内停车服务指数系统巡检人员执法分布详见图12所示。
路内停车服务指数发布与共享模块用于实时发布路内停车服务指数系统的信息发布与共享环境建立，通过依托路内停车管理服务指数平台，开展的城市路内停车服务指数的分析与挖掘，通过门户网站，实现路内停车服务实数的可视化成果发布与共享。
本申请实施例的实时发布路内停车服务指数方法及系统可以节省城市路内停车的停车时间与停车成本，提高路内停车服务的实效性与便捷性，既可以产生停车产业的直接效益，又可以产生停车服务的间接效益；可以通过构建实时发布路内停车服务指数的方法与系统，带动城市路内停车行业对新技术、新产品、新模式的应用发展，实现城市路内停车信息的增值服务与综合服务，产生路内停车领域产业链的商业价值与经济效益。
随着快速城市化建设进程的发展，城市道路交通拥挤、交通安全、交通污染问题越发严重，直接影响城市道路交通流的重要因素是停车问题；在城市中心区域交通流中有30％的车辆是寻找停车位、在全市域道路网络交通流中有20％的车辆是在寻找停车位而造成交通的拥堵；由于城市道路交通网络的路内停车方式因自身的停车便利、步行距离短等优点，受到车辆驾驶人员的普遍欢迎；实时发布路内停车服务指数的方法与系统是实现高效路内停车管理服务的核心所在，这对于缓解城市交通拥堵、提高公众出行安全、降低城市交通污染等都具有重要的社会价值。
本申请实施例的实时发布路内停车服务指数方法及系统发明专利将在深圳市交通运输委的“深圳市道路交通管理事物中心”承担智慧路内停车管理中得以应用实践。
截止2016年12月，深圳市人口总量超过2100万人，小汽车保有量超过322万台。机动化出行需求增长，全市全方式日均出行总量4443万人次，其中机动化出行总量2133万人次。全市机动化出行包括居民机动化出行和流动人口机动化出行。其中，全市居民日均机动化出行1910万人次，流动人口日均机动化出行223万人次。全市居民和流动人口日均机动化出行量分别占全市日均机动化出行总量的89.5％和10.5％。而城市路内停车泊位占有率提高，停车资源得到更高效利用，2016年全市在原特区内共计11158个路内停车泊位。其中罗湖区1247个；福田区5210个；南山区3847个；盐田区854个；车泊位占有率分别提升了14.1％、14.4％、13.4％、9.3％。罗湖区路内停车泊位占有率最高，达到了61.3％，不仅停车难问题得到了有效的缓解，而且城市道路网络交通流速度也得到大幅度提升。交通拥挤与共享停车环境的实时发布路内停车服务指数方法与系统针对道路停车收费管理的社会公众化服务特点，综合运用交通大数据、人工智能、射频通信、手机集群通信技术，实现城市道路路内停车泊位的在线监控模式，创建了精准研判、方便快捷、费用合理、执法有效的国家住房和城乡建设部的路内停车试点示范模式。
虽然本发明参照当前的较佳实施方式进行了描述，但本领域的技术人员应能理解，上述较佳实施方式仅用来说明本发明，并非用来限定本发明的保护范围，任何在本发明的精神和原则范围之内，所做的任何修饰、等效替换、改进等，均应包含在本发明的权利保护范围之内。

Claims (10)

  1. 一种实时发布路内停车服务指数方法，其特征在于，包括：
    步骤a：建立路内停车设置的车速阻滞模型；
    步骤b：分析路内停车带设置后机动车辆延误情况；
    步骤c：选择路内停车带合理设置规模；
    步骤d：规划城市路内停车设计。
  2. 根据权利要求1所述的实时发布路内停车服务指数方法，其特征在于，所述步骤a前还包括：建立路内停车服务指数指标体系，为路内停车的服务水平与服务质量的评估提供科学依据。
  3. 根据权利要求1或2所述的实时发布路内停车服务指数方法，其特征在于，所述步骤a具体包括：建立路段车速基本模型；建立路内停车带的摩擦效应修正模型；建立路内停车带的阻滞效应修正模型，其中，所述摩擦效应修正后的路段车速模型为：
    Figure PCTCN2017117094-appb-100001
    ki--基于空间障碍率影响斜率参数；
    所述摩擦效应与阻滞效应后的修正模型为：
    Figure PCTCN2017117094-appb-100002
    式中：k2--基于时间障碍率影响的待标定参数。
  4. 根据权利要求1所述的实时发布路内停车服务指数方法，其特征在于，所述步骤b具体包括：在机动车速阻滞模型建立的基础上，将摩擦效应和阻滞效应作为整体分析路内停车对路段机动车流的干扰，建立相应的理论模型，对路内停车设置后对路段交通流影响进行分析。
  5. 根据权利要求4所述的实时发布路内停车服务指数方法，其特征在于，所述建立相应的理论模型包括：减速-加速延误模型、跟驰延误模型、离散流情况下的跟驰延误模型、连续流情况下的跟驰延误模型、总延误模型建立与车 辆延误模型。
  6. 根据权利要求1所述的实时发布路内停车服务指数方法，其特征在于，所述步骤c具体包括：设置车辆停放者行为选择模型；设置车辆停放者成本模型；设置路段出行者出行成本模型；选择路内停车带合理规模；设计模型算法。
  7. 根据权利要求6所述的实时发布路内停车服务指数方法，其特征在于，所述设计的模型算法具体包括：
    步骤11：取初始步长ri＞0，允许误差e＞0；
    步骤12：找出一可行内点X(0)∈R0，并且令k＝1；
    步骤13：构造障碍函数，障碍项可采用导数函数：
    Figure PCTCN2017117094-appb-100003
    或对数函数形式：
    Figure PCTCN2017117094-appb-100004
    其中rk＞0；
    步骤14：以
    Figure PCTCN2017117094-appb-100005
    为初始点，对障碍函数进行无约束极小化(在R0内)：
    Figure PCTCN2017117094-appb-100006
    步骤15：检验是否满足收敛准则：
    Figure PCTCN2017117094-appb-100007
    或
    Figure PCTCN2017117094-appb-100008
    步骤16：如满足上述准则，则以X(k)为原问题的近似极小解Xmin；否则，取rk+1＜rk(取rk+1＝rk/10或rk/5)，令k＝k+1，转向步骤13继续进行迭代；
    步骤17：考虑到路内停车带位置在城市交通网络拥挤影响因素停车成本增加Y(t)＞0；
    步骤18：考虑到路内外停车位共享模式减少的路内停车成本G(t)＞0。
  8. 根据权利要求1所述的实时发布路内停车服务指数方法，其特征在于，所述步骤d包括：选择需要设置路内停车的路段，选择过程要根据道路交通条件与交通量状况对路段能否设置路内停车带做出初步判断；确定路内停车的设计目标：对设置条件进行分析；研究路内停车带合理位置的选择，分析路内停车带与信号交叉口和建筑物出入口及人行横道的间距关系，以及受地形条件及 特殊交通环境的限制；对路内停车带泊位的设计方法及其适用性进行研究，并在此基础上考察路内停车带的设置是否满足设计目标，如果不满足，则还需要重新设计路内停车带。
  9. 一种实时发布路内停车服务指数系统，其特征在于，所述实时发布路内停车服务指数系统包括系统前端监测模块、系统后台服务模块、系统数据分析与挖掘服务指数模块、路内停车服务指数发布与共享模块，所述系统前端监测模块用于完成路内停车车位使用状况信息的采集任务，所述系统后台服务模块用于构建路内停车管理服务指数平台，实现路内停车车位使用状况、路内停车服务纠错、交易处理与清分结算、停车用户管理服务巡检、信息处理报表生成与分析、预警方式可视化、路内停车数据存储与共享和/或系统运行维护，系统数据分析与挖掘服务指数模块用于完成系统运行监控、T-GIS电子地图精准定位匹配、路内停车车位数据分析和/或自动生成车位使用报表，所述路内停车服务指数发布与共享模块用于实时发布路内停车服务指数系统的信息发布与共享环境建立，实现路内停车服务实数的可视化成果发布与共享。
  10. 根据权利要求9所述的实时发布路内停车服务指数系统，其特征在于，所述系统前端监测模块包括路内停车车位地磁线圈检测器、无线射频通信、视频监控等前端信息采集终端。
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